In a typical cloud-based computing environment (e.g., a data center), multiple compute nodes may execute workloads (e.g., processes, applications, services, etc.) on behalf of customers. During the execution of the workloads, the amount of data storage capacity to be used for ephemeral data (e.g., cache or other data temporarily used by an application to perform operations) varies with the number and types of workloads executed by each compute node. Typically, such data is local to each compute node, either in one or more local solid state drives (SSD), hard disk drives (HDD), or other local data storage device and may be addressable in blocks (e.g., sets of bytes). To guard against the possibility of having inadequate local data storage for the ephemeral data storage needs of the workloads, each compute node is typically equipped with a fixed amount of data storage capacity to meet the peak amount that may occasionally be requested by the workloads. However, given the variations in the ephemeral data storage needs of the workloads as they are executed, the capacity of the local data storage devices may go unused for a significant percentage of the time, resulting in wasted resources in the data center.